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The paper describes the open Russian medical language understanding benchmark covering several task types (classification, question answering, natural language inference, named entity recognition) on a number of novel text sets.
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Shelmanov, A., Smirnov, I., Vishneva, E.: Information extraction from clinical texts in russian. In: Computational Linguistics and Intellectual Technologies. pp. 560–572 (2015)
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Johnson, A.E., Pollard, T.J., Shen, L., Li-Wei, H.L., Feng, M., Ghassemi, M., Moody, B., Szolovits, P., Celi, L.A., Mark, R.G.: Mimic-iii, a freely accessible critical care database. Scientific data 3
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Blinov, P., Avetisian, M., Kokh, V., Umerenkov, D., Tuzhilin, A.: Predicting clinical diagnosis from patients electronic health records using bert-based neural networks. In: Michalowski, M., Moskovitch, R. (eds.) Artificial Intelligence in Medicine. pp. 111–121. Springer International Publishing, Cham (2020)
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Lee, J., Yoon, W., Kim, S., Kim, D., Kim, S., So, C.H., Kang, J.: Biobert: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics 36
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Lewis, P., Ott, M., Du, J., Stoyanov, V.: Pretrained language models for biomedical and clinical tasks: Understanding and extending the state-of-the-art. In: Proceedings of the 3rd Clinical Natural Language Processing Workshop. pp. 146–157 (2020)
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Alsentzer, E., Murphy, J., Boag, W., Weng, W.H., Jin, D., Naumann, T., McDermott, M.: Publicly available clinical BERT embeddings. In: Proceedings of the 2nd Clinical Natural Language Processing Workshop. pp. 72–78. Association for Computational Linguistics, Minneapolis, Minnesota, USA (Jun 2019)
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2020
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Shavrina, T., Fenogenova, A., Anton, E., Shevelev, D., Artemova, E., Malykh, V., Mikhailov, V., Tikhonova, M., Chertok, A., Evlampiev, A.: RussianSuperGLUE: A Russian language understanding evaluation benchmark. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). pp. 4717–4726. Association for Computational Linguistics, Online (Nov 2020)
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Tutubalina, E., Alimova, I., Miftahutdinov, Z., Sakhovskiy, A., Malykh, V., Nikolenko, S.: The russian drug reaction corpus and neural models for drug reactions and effectiveness detection in user reviews. Bioinformatics (Jul 2020)
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Starovoytova, E.A., Kulikov, E.S., Fedosenko, S.V., Shmyrina, A.A., Kirillova, N.A., Vinokurova, D.A., Balaganskaya, M.A.: Rumedprimedata (Dec 2021). https://doi.org/10.5281/zenodo.5765873
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2021
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Blinov, P., Nesterov, A., Zubkova, G., Reshetnikova, A., Kokh, V., Shivade, C.: Rumednli: A russian natural language inference dataset for the clinical domain. PhysioNet (2022). https://doi.org/10.13026/gxzd-cf80
2022
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